|Detect BRISK features and return BRISKPoints object|
|Detect corners using FAST algorithm and return cornerPoints object|
|Detect corners using Harris–Stephens algorithm and return cornerPoints object|
|Detect corners using minimum eigenvalue algorithm and return cornerPoints object|
|Detect MSER features and return MSERRegions object|
|Detect SURF features and return SURFPoints object|
|Detect KAZE features|
Learn the benefits and applications of local feature detection and extraction
Choose functions that return and accept points objects for several types of features
Specify pixel Indices, spatial coordinates, and 3-D coordinate systems
Use local neighborhoods and the Harris algorithm to find corresponding interest points.
Use the SURF local feature detector function to find corresponding points between two images.
This example shows how to stabilize a video that was captured from a jittery platform.
This example shows how to detect a particular object in a cluttered scene, given a reference image of the object.
This example shows how to classify digits using HOG features and a multiclass SVM classifier.